This book focuses on how to calculate maximum likelihood estimates of the parameters of a multivariate linear model with correlated errors when some of the dependent variates are not measured on some of the experimental units. The author presents a computer program that obtains these estimates and can also be used to solve several well-known statistical models, including the multivariate linear regression model. Providing definitions and notations used in incomplete multivariate models, the author delves into the subject of maximum likelihood estimates and how they are calculated. Practical examples demonstrate the program, and the author addresses sample problems, issues, warnings, and error messages that may occur. With its clear explanations and illustrative examples, this book is a valuable resource for researchers and practitioners in statistics, econometrics, and related fields, as well as students studying these disciplines. By providing a user-friendly tool for obtaining maximum likelihood estimates in incomplete multivariate linear models, this book makes complex statistical calculations more accessible and efficient.
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Gebunden. Condition: New. KlappentextrnrnExcerpt from Missing: A Computer Program for the Maximum Likelihood Estimates of the Parameters of the Multivariate Linear Model With Incomplete MeasurementsOur procedure was developed to model the forest growth and yield . Seller Inventory # 2144782807
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